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Functional near-infrared spectroscopy (fNIRS) measures the functional activity of the cerebral cortex. The concentration changes of oxygenated (oxy-Hb) and deoxygenated hemoglobin (deoxy-Hb) can be detected and associated with activation of the cortex in the investigated area (neurovascular coupling). Recorded signals of hemodynamic responses may contain influences from physiological signals (systemic influences, physiological artifacts) which do not originate from the cerebral cortex activity. The physiological artifacts contain the blood pressure (BP), respiratory patterns, and the pulsation of the heart. In order to perform a comprehensive analysis of recorded fNIRS data, a proper correction of these physiological artifacts is necessary. This article introduces NICA – a novel toolbox for near-infrared spectroscopy calculations and analyses based on MATLAB. With NICA it is possible to process and visualize fNIRS data, including different signal processing methods for physiological artifact correction. The artifact correction methods used in this toolbox are common average reference (CAR), independent component analysis (ICA), and transfer function (TF) models. A practical example provides results from a study, where NICA was used for analyzing the measurement data, in order to demonstrate the signal processing steps and the physiological artifact correction. The toolbox was developed for fNIRS data recorded with the NIRScout 1624 measurement device and the corresponding recording software NIRStar.

Functional near-infrared spectroscopy (fNIRS) measures the functional activity of the cerebral cortex. The concentration changes of oxygenated (oxy-Hb) and deoxygenated hemoglobin (deoxy-Hb) can be detected and associated with activation of the cortex in the investigated area (neurovascular coupling). Recorded signals of hemodynamic responses may contain influences from physiological signals (systemic influences, physiological artifacts) which do not originate from the cerebral cortex activity. The physiological artifacts contain the blood pressure (BP), respiratory patterns, and the pulsation of the heart. In order to perform a comprehensive analysis of recorded fNIRS data, a proper correction of these physiological artifacts is necessary. This article introduces NICA – a novel toolbox for near-infrared spectroscopy calculations and analyses based on MATLAB. With NICA it is possible to process and visualize fNIRS data, including different signal processing methods for physiological artifact correction. The artifact correction methods used in this toolbox are common average reference (CAR), independent component analysis (ICA), and transfer function (TF) models. A practical example provides results from a study, where NICA was used for analyzing the measurement data, in order to demonstrate the signal processing steps and the physiological artifact correction. The toolbox was developed for fNIRS data recorded with the NIRScout 1624 measurement device and the corresponding recording software NIRStar. [ABSTRACT FROM AUTHOR]